Brain data#

This section presents results of brain MRI data. Below are quantitative T1 values computed using the MP2RAGE and the MTsat methods. These values are averaged within the gray matter and white matter masks.

Code imports#

# Python imports 
from IPython.display import clear_output
from pathlib import Path
import numpy as np

import pandas as pd
pd.set_option('display.max_rows', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.width', 1000)
pd.set_option('display.colheader_justify', 'center')
pd.set_option('display.precision', 1)

# Import custom tools
from tools.data import Data
from tools.plot import Plot
from tools.stats import Stats

Download data#

data_type = 'brain'
release_version = 'latest'

dataset = Data(data_type)
dataset.download(release_version)
--2023-02-08 16:29:51--  https://github.com/courtois-neuromod/anat-processing/releases/download/r20220921/neuromod-anat-brain-qmri.zip
Resolving github.com (github.com)... 140.82.114.3
Connecting to github.com (github.com)|140.82.114.3|:443... connected.
HTTP request sent, awaiting response... 
302 Found
Location: https://objects.githubusercontent.com/github-production-release-asset-2e65be/333825187/59a68bb3-4423-49ab-959d-247690acbebc?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWNJYAX4CSVEH53A%2F20230208%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20230208T162952Z&X-Amz-Expires=300&X-Amz-Signature=deb6725212c9494f54456b0217bef2cdcd09ab776e20281951bcb71efed30f81&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=333825187&response-content-disposition=attachment%3B%20filename%3Dneuromod-anat-brain-qmri.zip&response-content-type=application%2Foctet-stream [following]
--2023-02-08 16:29:52--  https://objects.githubusercontent.com/github-production-release-asset-2e65be/333825187/59a68bb3-4423-49ab-959d-247690acbebc?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWNJYAX4CSVEH53A%2F20230208%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20230208T162952Z&X-Amz-Expires=300&X-Amz-Signature=deb6725212c9494f54456b0217bef2cdcd09ab776e20281951bcb71efed30f81&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=333825187&response-content-disposition=attachment%3B%20filename%3Dneuromod-anat-brain-qmri.zip&response-content-type=application%2Foctet-stream
Resolving objects.githubusercontent.com (objects.githubusercontent.com)... 185.199.108.133, 185.199.110.133, 185.199.109.133, ...
Connecting to objects.githubusercontent.com (objects.githubusercontent.com)|185.199.108.133|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 1301347 (1.2M) [application/octet-stream]
Saving to: ‘neuromod-anat-brain-qmri.zip’

     0K .......... .......... .......... .......... ..........  3% 5.27M 0s
    50K .......... .......... .......... .......... .....
Archive:  neuromod-anat-brain-qmri.zip
  inflating: data/brain/neuromod-anat-brain.nextflow.log  
  inflating: data/brain/results-neuromod-anat-brain-qmri.csv  
  inflating: data/brain/._results-neuromod-anat-brain-qmri.csv  
  inflating: data/brain/dag.dot      
  inflating: data/brain/report.html  
  inflating: data/brain/dag.png      
.....  7% 6.91M 0s
   100K .......... .......... .......... .......... .......... 11% 20.3M 0s
   150K .......... .......... .......... .......... .......... 15%  110M 0s
   200K .......... .......... .......... .......... .......... 19% 7.94M 0s
   250K .......... .......... .......... .......... .......... 23%  129M 0s
   300K .......... .......... .......... .......... .......... 27% 43.4M 0s
   350K .......... .......... .......... .......... .......... 31% 82.2M 0s
   400K .......... .......... .......... .......... .......... 35%  113M 0s
   450K .......... .......... .......... .......... .......... 39% 58.2M 0s
   500K .......... .......... .......... .......... .......... 43% 10.2M 0s
   550K .......... .......... .......... .......... .......... 47% 69.4M 0s
   600K .......... .......... .......... .......... .......... 51%  132M 0s
   650K .......... .......... .......... .......... .......... 55%  132M 0s
   700K .......... .......... .......... .......... .......... 59% 77.3M 0s
   750K .......... .......... .......... .......... .......... 62% 88.9M 0s
   800K .......... .......... .......... .......... .......... 66% 94.8M 0s
   850K .......... .......... .......... .......... .......... 70% 97.6M 0s
   900K .......... .......... .......... .......... .......... 74%  121M 0s
   950K .......... .......... .......... .......... .......... 78%  119M 0s
  1000K .......... .......... .......... .......... .......... 82%  128M 0s
  1050K .......... .......... .......... .......... .......... 86%  124M 0s
  1100K .......... .......... .......... .......... .......... 90% 17.8M 0s
  1150K .......... .......... .......... .......... .......... 94%  246M 0s
  1200K .......... .......... .......... .......... .......... 98% 21.1M 0s
  1250K .......... ..........                                 100%  426M=0.04s

2023-02-08 16:29:52 (28.2 MB/s) - ‘neuromod-anat-brain-qmri.zip’ saved [1301347/1301347]

Load data plot it#

qMRI Metrics#

dataset.load()
fig_gm = Plot(dataset, plot_name = 'brain-1')

fig_gm.title = 'Brain qMRI microstructure measures'
# If you're running this notebook in a Jupyter Notebook (eg, on MyBinder), change 'jupyter-book' to 'notebook'
fig_gm.display('jupyter-book')

Statistics#

White Matter#

stats_wm = Stats(dataset)
stats_wm.build_df('WM')
stats_wm.build_stats_table()
display(stats_wm.stats_table)
T1 (MP2RAGE) T1 (MTsat) MTR MTsat
intrasubject COV mean [%] 0.6 2.3 0.6 1.7
intrasubject COV std [%] 0.2 0.8 0.1 0.5
intersubject mean COV [%] 1.9 3.5 0.4 2.2

Grey Matter#

stats_gm = Stats(dataset)
stats_gm.build_df('GM')
stats_gm.build_stats_table()
display(stats_gm.stats_table)
T1 (MP2RAGE) T1 (MTsat) MTR MTsat
intrasubject COV mean [%] 0.4 3.1 0.8 2.7
intrasubject COV std [%] 0.1 1.6 0.2 1.2
intersubject mean COV [%] 1.0 5.7 1.2 4.5

Diffusion#

data_type = 'brain-diffusion-cc'
release_version = 'latest'

dataset = Data(data_type)
dataset.download(release_version)
--2023-02-08 16:29:54--  https://github.com/courtois-neuromod/anat-processing/releases/download/r20230110/brain-diffusion-cc.zip
Resolving github.com (github.com)... 140.82.114.3
Connecting to github.com (github.com)|140.82.114.3|:443... connected.
HTTP request sent, awaiting response... 
302 Found
Location: https://objects.githubusercontent.com/github-production-release-asset-2e65be/333825187/6e6dd34d-c009-4079-bea8-df5eea106c89?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWNJYAX4CSVEH53A%2F20230208%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20230208T162954Z&X-Amz-Expires=300&X-Amz-Signature=ab0d7bf61cc702405f070849b86587aa89e2b32281119fe4105071ac2f385672&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=333825187&response-content-disposition=attachment%3B%20filename%3Dbrain-diffusion-cc.zip&response-content-type=application%2Foctet-stream [following]
--2023-02-08 16:29:54--  https://objects.githubusercontent.com/github-production-release-asset-2e65be/333825187/6e6dd34d-c009-4079-bea8-df5eea106c89?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWNJYAX4CSVEH53A%2F20230208%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20230208T162954Z&X-Amz-Expires=300&X-Amz-Signature=ab0d7bf61cc702405f070849b86587aa89e2b32281119fe4105071ac2f385672&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=333825187&response-content-disposition=attachment%3B%20filename%3Dbrain-diffusion-cc.zip&response-content-type=application%2Foctet-stream
Resolving objects.githubusercontent.com (objects.githubusercontent.com)... 185.199.109.133, 185.199.111.133, 185.199.108.133, ...
Connecting to objects.githubusercontent.com (objects.githubusercontent.com)|185.199.109.133|:443... connected.
HTTP request sent, awaiting response... 
Archive:  brain-diffusion-cc.zip
  inflating: data/brain-diffusion-cc/labels.py  
  inflating: data/brain-diffusion-cc/._labels.py  
  inflating: data/brain-diffusion-cc/.DS_Store  
  inflating: data/brain-diffusion-cc/._.DS_Store  
  inflating: data/brain-diffusion-cc/labels.ipynb  
  inflating: data/brain-diffusion-cc/._labels.ipynb  
  inflating: data/brain-diffusion-cc/corpus_callosum-metrics.csv  
  inflating: data/brain-diffusion-cc/._corpus_callosum-metrics.csv  
200 OK
Length: 15248 (15K) [application/octet-stream]
Saving to: ‘brain-diffusion-cc.zip’

     0K .......... ....                                       100% 27.2M=0.001s

2023-02-08 16:29:54 (27.2 MB/s) - ‘brain-diffusion-cc.zip’ saved [15248/15248]
dataset.load()

fig_diff = Plot(dataset, plot_name = 'brain-diff-cc')

fig_diff.title = 'Brain qMRI diffusion measures - corpus callosum'

fig_diff.display('jupyter-book')

Statistics#

Genu#

stats_cc1 = Stats(dataset)
stats_cc1.build_df('genu')
stats_cc1.build_stats_table()
display(stats_cc1.stats_table)
FA (DWI) MD (DWI) RD (DWI)
intrasubject COV mean [%] 0.8 1.0 1.3
intrasubject COV std [%] 0.3 0.6 0.6
intersubject mean COV [%] 4.2 6.2 10.3

Body#

stats_cc1 = Stats(dataset)
stats_cc1.build_df('body')
stats_cc1.build_stats_table()
display(stats_cc1.stats_table)
FA (DWI) MD (DWI) RD (DWI)
intrasubject COV mean [%] 0.6 0.7 0.7
intrasubject COV std [%] 0.2 0.2 0.3
intersubject mean COV [%] 3.8 3.0 6.2

Splenium#

stats_cc1 = Stats(dataset)
stats_cc1.build_df('splenium')
stats_cc1.build_stats_table()
display(stats_cc1.stats_table)
FA (DWI) MD (DWI) RD (DWI)
intrasubject COV mean [%] 0.6 0.7 0.8
intrasubject COV std [%] 0.1 0.2 0.3
intersubject mean COV [%] 2.6 3.1 6.3